A modeling strategy for the dose-escalation Phase I trials with a large number of combination-schedules

Music City Center 

There is an increasing interest in the development of the combinations of several drugs that can enhance the efficacy of each of the compounds compared to when administered as monotherapies. These could be combinations of a new experimental agent with an approved (or at least well-studied) compound or a combination of two new experimental agents. In either case, the selection of the optimal dose level of one agent might depend on the dose level of another agent. This implies that these two should be optimised together. Furthermore, the toxicity and efficacy of the combination might be different when its is administered under different schedules. In total, the doses of two agents and their administration schedule should be administered simultaneously resulting in a 3-dimensional dose-escalation problem with potentially many combination-schedule levels to be tried. Due to these challenges, it is common to restrict the search with at least one compound being fixed. This, however, can result in suboptimal selection of the combination-schedule. In this talk, motivating by a real trial, we will introduce a novel dose-escalation design that partitions the 3-dimensional grid of combination-schedules into smaller sub-grids and fits a combination-schedule-toxicity model within each. Then, via model-averaging between these models, the estimates for the whole 3-dimensional grid are obtained. We will show that under a number of considered cases, the proposed design results in better accuracy than other model-based designs that attempt to model the whole grid altogether.